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Health Professions faculty receive research funding

Congratulations to the Health Professions faculty whose research projects were selected for Tier 3 funding of the UM System’s Research and Creative Works Strategic Investment. This initiative aims to invest in research and creative works over the next five years to support and address grand challenges, foster collaboration systemwide and provide instrumentation to enhance faculty research. 

The UM System received 74 formal proposals for Tier 3 funding, and the 23 projects that were awarded the highest ranks were approved. Six of nine Health Professions research proposals received funding.

Below, in alphabetical order, are the six projects created by seven Health Professions faculty members that were awarded funding. Congratulations! 

Measurement Error and Bias in Estimating Legal Status
PI: Claire Altman (HEALTH SCIENCES)
Understand characteristics of foreign-born populations by legal status and examine how this affects integration outcomes. The project uses survey data from the U.S. Census and federal administrative records.

Dynamics of Native Language Change in L2 Learners
PI: Mona Botezatu (SLHS)
Explore language processing dynamics in adults during the early stages of learning a second language. The goal of the project is to determine how the timing of the shift away from monolingual processing patterns relates to individual differences in second-language proficiency levels, cognitive resources and language pairings.

Health Care Transition Planning for Youth with Autism
PI: Nancy Cheak-Zamora (HEALTH SCIENCES)
Develop and validate a caregiver-reported human-robot interaction measure based on young adults with Autism Spectrum Disorders and caregiver input to ensure adequate health care transition services. The conclusion of this study will result in a usable electronic tool that can be immediately implemented in the health care system.

Addressing Homelessness: A Potential AI Application
PI: Hsun-Ta Hsu (SOCIAL WORK)
CO-PI: Jianlin Cheng (ENGINEERING-COMPUTER SCIENCE)
Apply artificial intelligence and machine learning to develop efficient and fair housing prioritization tools for individuals and families experiencing homelessness. The data collection tool will be able to inform health policy development and service delivery.

Look Around: Youth Participatory Action Research
PI: Clark Peters (SOCIAL WORK)
CO-PI: David Aguayo (EDUCATION)
Design a culturally responsive social media campaign with the goal to improve mental health stigma and help-seeking among Black youth. The project will use Youth Participatory Action Research to develop and implement a culturally enhanced campaign with middle and high school Black students in Boone County.

Timing and Language in Dialogue
PI: Nicholas Smith (SLHS)
CO-PIs: Jean M. Ispa (HES-HDFS), Elizabeth S. Kelley (SLHS)
Examine mother-child dialogue in families who took part in the Early Head Start Research and Evaluation Program.